I'm a Research Fellow at the Center for Engineering in Medicine at Massachusetts General Hospital and Harvard Medical School. I'm working on finding new ways to diagnose and monitor treatment of cancer and infectious disease.
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DNA and protein microarrays are a high-throughput technology that allow the simultaneous quantification of tens of thousands of different biomolecular species. The mediocre sensitivity and limited dynamic range of traditional fluorescence microarrays compared to other detection techniques have been the technology’s Achilles’ heel and prevented their adoption for many biomedical and clinical diagnostic applications. Previous work to enhance the sensitivity of microarray readout to the single-molecule (“digital”) regime have either required signal amplifying chemistry or sacrificed throughput, nixing the platform’s primary advantages. Here, we report the development of a digital microarray which extends both the sensitivity and dynamic range of microarrays by about 3 orders of magnitude. This technique uses functionalized gold nanorods as single-molecule labels and an interferometric scanner which can rapidly enumerate individual nanorods by imaging them with a 10× objective lens. This approach does not require any chemical signal enhancement such as silver deposition and scans arrays with a throughput similar to commercial fluorescence scanners. By combining single-nanoparticle enumeration and ensemble measurements of spots when the particles are very dense, this system achieves a dynamic range of about 6 orders of magnitude directly from a single scan. As a proof-of-concept digital protein microarray assay, we demonstrated detection of hepatitis B virus surface antigen in buffer with a limit of detection of 3.2 pg/mL. More broadly, the technique’s simplicity and high-throughput nature make digital microarrays a flexible platform technology with a wide range of potential applications in biomedical research and clinical diagnostics.
The sensitive detection and quantitative measurement of biological nanoparticles such as viruses or exosomes is of growing importance in biology and medicine since these structures are implicated in many biological processes and diseases. Interferometric reflectance imaging is a label-free optical biosensing method which can directly detect individual biological nanoparticles when they are immobilized onto a protein microarray. Previous efforts to infer bio-nanoparticle size and shape have relied on empirical calibration using a 'ruler' of particle samples of known size, which was inconsistent and qualitative. Here, we present a mechanistic physical explanation and experimental approach by which interferometric reflectance imaging may be used to not only detect but also quantitatively measure bio-nanoparticle size and shape. We introduce a comprehensive optical model that can quantitatively simulate the scattering of arbitrarily-shaped nanoparticles such as rod-shaped or filamentous virions. Finally, we optimize the optical design for the detection and quantitative measurement of small and low-index bio-nanoparticles immersed in water.
Single-molecule and single-nanoparticle biosensors are a growing frontier in diagnostics. Digital biosensors are those which enumerate all specifically immobilized biomolecules or biological nanoparticles, and thereby achieve limits of detection usually beyond the reach of ensemble measurements. Here, we review modern optical techniques for single nanoparticle detection and describe the single-particle interferometric reflectance imaging sensor (SP-IRIS). We present challenges associated with reliably detecting faint nanoparticles with SP-IRIS, and describe image acquisition processes and software modifications to address them. Specifically, we describe an image acquisition processing method for the discrimination and accurate counting of nanoparticles that greatly reduce both the number of false positives and false negatives. These engineering improvements are critical steps in the translation of SP-IRIS toward applications in medical diagnostics.
Biological nanoparticles such as viruses and exosomes are important biomarkers for a range of medical conditions, from infectious diseases to cancer. Biological sensors that detect whole viruses and exosomes with high specificity, yet without additional labeling, are promising because they reduce the complexity of sample preparation and may improve measurement quality by retaining information about nanoscale physical structure of the bio-nanoparticle (BNP). Towards this end, a variety of BNP biosensor technologies have been developed, several of which are capable of enumerating the precise number of detected viruses or exosomes and analyzing physical properties of each individual particle. Optical imaging techniques are promising candidates among broad range of label-free nanoparticle detectors. These imaging BNP sensors detect the binding of single nanoparticles on a flat surface functionalized with a specific capture molecule or an array of multiplexed capture probes. The functionalization step confers all molecular specificity for the sensor’s target but can introduce an unforeseen problem; a rough and inhomogeneous surface coating can be a source of noise, as these sensors detect small local changes in optical refractive index. In this paper, we review several optical technologies for label-free BNP detectors with a focus on imaging systems. We compare the surface-imaging methods including dark-field, surface plasmon resonance imaging and interference reflectance imaging. We discuss the importance of ensuring consistently uniform and smooth surface coatings of capture molecules for these types of biosensors and finally summarize several methods that have been developed towards addressing this challenge.
Label-free imaging of individual viruses and nanoparticles directly in complex solutions is important for virology research and biosensing applications. A successful visualization technique should be rapid, sensitive, and inexpensive, while needing minimal sample preparation or user expertise. Current approaches typically require fluorescent labeling or the use of an electron microscope, which are expensive and time-consuming to use. We have developed an imaging technique for real-time, sensitive, and label-free visualization of viruses and nanoparticles directly in complex solutions such as serum. By combining the advantages of a single-particle reflectance imaging sensor, with microfluidics, we perform real-time digital detection of individual 100 nm vesicular stomatitis viruses as they bind to an antibody microarray. Using this approach, we have shown capture and visualization of a recombinant vesicular stomatitis virus Ebola model (rVSV-ZEBOV) at 100 PFU/mL in undiluted fetal bovine serum in less than 30 min.
We have developed a robust and rapid computational method for processing the raw spectral data collected from thin film optical interference biosensors. We have applied this method to Interference Reflectance Imaging Sensor (IRIS) measurements and observed a 10,000 fold improvement in processing time, unlocking a variety of clinical and scientific applications. Interference biosensors have advantages over similar technologies in certain applications, for example highly multiplexed measurements of molecular kinetics. However, processing raw IRIS data into useful measurements has been prohibitively time consuming for high-throughput studies. Here we describe the implementation of a lookup table (LUT) technique that provides accurate results in far less time than naive methods. We also discuss an additional benefit that the LUT method can be used with a wider range of interference layer thickness and experimental configurations that are incompatible with methods that require fitting the spectral response.
The growth plate is a highly organized section of cartilage in the long bones of growing children that is susceptible to mechanical failure as well as structural and functional disruption caused by a dietary deficiency of vitamin D. The shear mechanical properties of the proximal tibial growth plate of rats raised either on normal or vitamin D and calcium deficient diets were measured. A sinusoidal oscillating shear load was applied to small excised growth plate specimens perpendicular to the direction of growth while imaging the deformation in real time with a fast confocal microscope. Local deformations and shear strains were quantified using image correlation. The proliferative zone of the growth plate bores the majority of the shear strain and the resting, hypertrophic and calcification zones deformed less. Surprisingly, we regularly observed discontinuous deformations in the proliferative zone in both groups that resembled cell columns sliding past one another in the direction of growth. These discontinuities manifested as regions of concentrated longitudinal shear strain. Furthermore, these shear strain concentrations were spaced evenly in the proliferative zone and the spacing between them was similar across growth plate regions and across control specimens. In contrast to the healthy controls, the vitamin D deficient growth plate exhibited larger variations in the size and orientation of cellular columns in the proliferative and hypertrophic zones. High strains were observed between columns, much as they were in the controls. However, the regular spacing of shear strain concentrations was not preserved, echoing the observation of decreased structural organization.
IRIS Processing is a MATLAB utility for making high-throughput measurements with IRIS, a label-free biosensing technology. It's described in this paper. If you're interested in IRIS Processing or wave optics in general, you might also be interested in this interactive implementation of the reflectance of thin films.
SP-IRIS-BEM is a collection of MATLAB functions for simulating single-nanoparticles imaged with IRIS, using the excellent Metallic Nanoparticle Boundary Element Method (MNPBEM) toolbox developed by others. It's described in this paper.
Micro-manager is an open-source software toolkit for controlling scientific microscopes. The below hardware adapters aren't part of the core micro-manager project but they are all BSD licensed, so feel free to use & improve them if they'll help your microscopy application: